rm(list=ls())
library(vegan)
library(psych)##
library(igraph)
library(beepr)
setwd("/Users/chenggao/Google_Drive/EPICON.NC.2022")
load("Bac.Fung.data.prep.stopby8datasets.amfL.RSLZxBF.Rarefaction.2021.08.13.rdata")
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
fq <- 7; abu <- 19;
SpMan<-function(fq, abu, treatment, tpA, tpB){
d1 <- d1.raw [env.R$Treatment1==treatment & env.R$TP > tpA & env.R$TP < tpB , ]
d1 <- d1 [,specnumber(t(d1)) > fq & colSums(d1)> abu]
d2 <- d2.raw [env.R$Treatment1==treatment & env.R$TP > tpA & env.R$TP < tpB, ]
d2 <- d2[, specnumber(t(d2)) > fq & colSums(d2)> abu]
env.R.tmp0 <- env.R [env.R$Treatment1==treatment & env.R$TP > tpA & env.R$TP < tpB , ]
d3 <- d3.raw [env.Z$Treatment1==treatment & env.Z$TP > tpA & env.Z$TP < tpB , ]
d3 <- d3 [,specnumber(t(d3)) > fq & colSums(d3)> abu]
d4 <- d4.raw [env.Z$Treatment1==treatment & env.Z$TP > tpA & env.Z$TP < tpB , ]
d4 <- d4 [,specnumber(t(d4)) > fq & colSums(d4)> abu]
env.Z.tmp0 <- env.Z [env.Z$Treatment1==treatment & env.Z$TP > tpA & env.Z$TP < tpB , ]
d5 <- d5.raw [env.S$Treatment1==treatment & env.S$TP > tpA & env.S$TP < tpB, ]
d5 <- d5[, specnumber(t(d5)) > fq & colSums(d5)> abu]
d6 <- d6.raw [env.S$Treatment1==treatment & env.S$TP > tpA & env.S$TP < tpB , ]
d6 <- d6 [,specnumber(t(d6)) > fq & colSums(d6)> abu]
env.S.tmp0 <- env.S [env.S$Treatment1==treatment & env.S$TP > tpA & env.S$TP < tpB , ]
d7 <- d7.raw [env.L$Treatment1==treatment & env.L$TP > tpA & env.L$TP < tpB , ]
d7 <- d7[,specnumber(t(d7)) > fq & colSums(d7)> abu]
d8 <- d8.raw [env.L$Treatment1==treatment & env.L$TP > tpA & env.L$TP < tpB, ]
d8 <- d8[, specnumber(t(d8)) > fq & colSums(d8)> abu]
env.L.tmp0 <- env.L [env.L$Treatment1==treatment & env.L$TP > tpA & env.L$TP < tpB , ]
saveRDS(env.L.tmp0, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.env.Leaf.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(env.S.tmp0, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.env.Soil.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(env.Z.tmp0, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.env.Rhizosphere.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(env.R.tmp0, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.env.Root.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d1, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.bac.Root.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d2, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.fung.Root.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d3, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.bac.Rhizosphere.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d4, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.fung.Rhizosphere.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d5, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.bac.Soil.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d6, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.fung.Soil.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d7, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.bac.Leaf.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
saveRDS(d8, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.fung.Leaf.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
d12<-cbind(d1,d2)
spman.d12 = corr.test(d12, use="pairwise",method="spearman",adjust="fdr", alpha=.05, ci=FALSE)
saveRDS(spman.d12, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/SpMan.crossBF.Root.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
d34<-cbind(d3,d4)
spman.d34 = corr.test(d34, use="pairwise",method="spearman",adjust="fdr", alpha=.05, ci=FALSE)
saveRDS(spman.d34, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/SpMan.crossBF.Rhizosphere.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
d56<-cbind(d5,d6)
spman.d56 = corr.test(d56, use="pairwise",method="spearman",adjust="fdr", alpha=.05, ci=FALSE)
saveRDS(spman.d56, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/SpMan.crossBF.Soil.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
d78<-cbind(d7,d8)
spman.d78 = corr.test(d78, use="pairwise",method="spearman",adjust="fdr", alpha=.05, ci=FALSE)
saveRDS(spman.d78, paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/SpMan.crossBF.Leaf.", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
beep()
}
#SpMan(fq, abu, "Control", 2, 9)
#SpMan(fq, abu, "Pre_flowering_drought", 2, 9)
#SpMan(fq, abu, "Control", 8, 18)
#SpMan(fq, abu, "Pre_flowering_drought", 8, 18)
#SpMan(fq, abu, "Control", 9, 18)
#SpMan(fq, abu, "Post_flowering_drought", 9, 18)
######################################
# significant positive correlations #
#####################################
setwd("/Users/chenggao/Google_Drive/EPICON.NC.2022")
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
r.cutoff = 0.6
p.cutoff = 0.05
SpMan.Rsig<-function(fq, abu, habitat, treatment, tpA, tpB){
d1 <- readRDS(paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.bac.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
d2 <- readRDS(paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/data.fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
d12 <- data.frame(d1, d2)
spman.r0 <- readRDS(paste0("Fig.3/BFT.SpMan.sig.df.FDR.padj.2022.05.31/SpMan.crossBF.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
Cor<-as.matrix(spman.r0$r)
Cor.df<-data.frame(row=rownames(Cor)[row(Cor)[upper.tri(Cor)]],
col=colnames(Cor)[col(Cor)[upper.tri(Cor)]], Cor=Cor[upper.tri(Cor)])
P0<-as.matrix(spman.r0$p)
P.df<-data.frame(row=rownames(P0)[row(P0)[upper.tri(P0)]],
col=colnames(P0)[col(P0)[upper.tri(P0)]], p=P0[upper.tri(P0)])
df <- data.frame(Cor.df, P.df, Habitat = habitat, Treatment = treatment, TPA = tpA)
da.tmp<-df.sig<- df[ df$Cor > r.cutoff & df$p < p.cutoff,]
V1<-data.frame("v1"=da.tmp$row); V2<-data.frame("v2"=da.tmp$col)
IDsub1<-ID.tmp[ID.tmp$OTU.ID %in% V1$v1, ]; IDsub2<-ID.tmp[ID.tmp$OTU.ID %in% V2$v2, ]
V1$id <- 1:nrow(V1); V2$id <- 1:nrow(V2)
M1<-merge(V1, IDsub1, by.x = "v1", by.y = "OTU.ID", all.x= T); M1<-M1[order(M1$id), ]
M2<-merge(V2, IDsub2, by.x = "v2", by.y = "OTU.ID", all.x = T); M2<-M2[order(M2$id), ]
df.tmp<-data.frame(da.tmp, M1, M2)
saveRDS(df.tmp, paste0("Fig.3/BFT.SpMan.sig.df.2022.05.31/SpMan.Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
}
#SpMan.Rsig(fq, abu,"Root", "Control", 2, 9)
#SpMan.Rsig(fq, abu,"Root", "Pre_flowering_drought", 2, 9)
#SpMan.Rsig(fq, abu,"Root", "Control", 8, 18)
#SpMan.Rsig(fq, abu,"Root", "Pre_flowering_drought", 8, 18)
#SpMan.Rsig(fq, abu,"Rhizosphere", "Control", 2, 9)
#SpMan.Rsig(fq, abu,"Rhizosphere", "Pre_flowering_drought", 2, 9)
#SpMan.Rsig(fq, abu,"Rhizosphere", "Control", 8, 18)
#SpMan.Rsig(fq, abu,"Rhizosphere", "Pre_flowering_drought", 8, 18)
#SpMan.Rsig(fq, abu,"Soil", "Control", 2, 9)
#SpMan.Rsig(fq, abu,"Soil", "Pre_flowering_drought", 2, 9)
#SpMan.Rsig(fq, abu,"Soil", "Control", 8, 18)
#SpMan.Rsig(fq, abu,"Soil", "Pre_flowering_drought", 8, 18)
#SpMan.Rsig(fq, abu,"Leaf", "Control", 2, 9)
#SpMan.Rsig(fq, abu,"Leaf", "Pre_flowering_drought", 2, 9)
#SpMan.Rsig(fq, abu,"Leaf", "Control", 8, 18)
#SpMan.Rsig(fq, abu,"Leaf", "Pre_flowering_drought", 8, 18)
library(vegan)
library(psych)##
library(igraph)
library(beepr)
library(igraph)
setwd("/Users/chenggao/Google_Drive/EPICON.NC.2022")
load("Bac.Fung.data.prep.stopby8datasets.amfL.RSLZxBF.Rarefaction.2021.08.13.rdata")
####################
# Module cross BF###
####################
bac.fung.cross.module.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
da<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
g <- graph.data.frame(da, directed=FALSE)
fun.fc<-cluster_fast_greedy(g)
print(modularity(fun.fc))
modularity(fun.fc,membership(fun.fc))
membership(fun.fc)
print(sizes(fun.fc))###
fun.comps <- membership(fun.fc)
colbar <-c("#0000FF","#FF3399","#FFCC33","#9999FF", "#FF99FF", "#FFFFCC",
"#33FFFF","#CCFF00","#CCFFCC","#FF3300","#CC99CC","#CC66CC","#FFFFCC","#CC0033","#666666","slateblue1","springgreen","steelblue1","tan1","thistle1","tomato","turquoise", "violet", "red", "yellowgreen","peachpuff", "peru", "pink", "plum2", "purple","wheat", "cornsilk3","cornsilk","coral4","coral",
"chocolate4","chocolate","black","chartreuse4","chartreuse","burlywood4","burlywood","brown4","blue","bisque4","bisque",
"azure4","azure","aquamarine4","aquamarine","antiquewhite4","antiquewhite","aliceblue","dodgerblue4","dodgerblue","dimgrey",
"deepskyblue4", "deepskyblue", "deeppink4", "deeppink","darkviolet", "darkslategray4","darkslategray",
"darkseagreen4", "darkseagreen", "darksalmon", "darkred", "darkorchid4", "darkorchid", "darkorange4",
"darkorange","firebrick","darkgreen", "darkgoldenrod4","grey", "darkgoldenrod", "darkcyan")
V(g)$color <- colbar[fun.comps]
set.seed(123)
plot(g, edge.width=0.5,edge.color="grey", vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=3,margin=c(0, 0,0,0))
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
bac.fung.cross.module.net("SpMan",fq, abu,"Root","Control", 2, 9)
## [1] 0.5190281
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
## 223 332 113 17 2 3 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
## [1] 0.8119668
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 12 15 6 4 4 6 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 27 28 29 30 31 32 33
## 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Root","Control", 8, 18)
## [1] 0.4485985
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 126 180 41 13 9 5 6 5 4 3 3 2 2 2 2 2 2 2 2 2
## 21 22 23 24 25 26 27 28 29 30
## 2 2 2 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
## [1] 0.3723379
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 285 183 86 7 3 2 2 2 3 2 3 2 2 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
## [1] 0.4582705
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 189 308 359 16 10 9 5 7 5 6 32 2 2 3 3 3 4 3 3 3
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51
## 2 2 2 2 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
## [1] 0.6884142
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 34 59 76 24 17 26 10 12 6 5 3 5 5 4 4 4 3 3 3 3 3 3 3 3 3 3
## 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 79 80 81 82 83
## 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
## [1] 0.4815539
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 279 356 104 20 8 11 4 5 4 4 3 3 2 4 2 3 3 3 3 3
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
## [1] 0.32127
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 219 305 260 55 4 3 6 2 3 2 3 2 2 2 2 2 2 2 2 2
## 21 22 23 24 25 26 27
## 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Soil","Control", 2, 9)
## [1] 0.6840684
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 176 91 30 117 29 19 11 8 7 6 6 5 5 5 5 5 4 4 6 4
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 3 3 3 4 4 3 3 3 3 3 3 3 3 3 3 3 3 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 121 122 123 124 125 126 127 128 129 130 131 132 133
## 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
## [1] 0.8380596
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 36 32 12 14 7 6 5 7 4 4 4 4 4 3 3 3 3 4 3 3 3 3 3 3 3 3
## 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Soil","Control", 8, 18)
## [1] 0.7882476
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 129 114 109 32 31 31 22 19 13 10 7 6 6 11 8 5 4 4 4 8
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 5 5 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 101 102 103 104
## 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
## [1] 0.6932747
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 177 157 119 40 27 20 12 6 7 7 6 5 3 3 3 3 3 3 3 3
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 81 82 83 84 85 86
## 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
## [1] 0.7427912
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
## 12 8 6 15 6 4 3 3 3 3 2 2 2 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
## [1] 0.6853
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
## 23 15 17 16 10 7 4 4 7 3 3 3 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
## [1] 0.4014326
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11
## 43 18 20 5 5 5 8 2 2 2 2
bac.fung.cross.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
## [1] 0.3305583
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12
## 51 55 58 12 2 2 2 2 2 2 2 2
#####################
# Module fung-fung###
####################
fung.module.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
da0<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
da <- da0[da0$Kingdom == "Eukaryote" & da0$Kingdom.1 == "Eukaryote",]
g <- graph.data.frame(da, directed=FALSE)
fun.fc<-cluster_fast_greedy(g)
print(modularity(fun.fc))
modularity(fun.fc,membership(fun.fc))
membership(fun.fc)
print(sizes(fun.fc))###
fun.comps <- membership(fun.fc)
colbar <-c("#0000FF","#FF3399","#FFCC33","#9999FF", "#FF99FF", "#FFFFCC",
"#33FFFF","#CCFF00","#CCFFCC","#FF3300","#CC99CC","#CC66CC","#FFFFCC","#CC0033","#666666","slateblue1","springgreen","steelblue1","tan1","thistle1","tomato","turquoise", "violet", "red", "yellowgreen", "peachpuff", "peru", "pink", "plum2", "purple","wheat", "cornsilk3","cornsilk","coral4","coral",
"chocolate4","chocolate","black","chartreuse4","chartreuse","burlywood4","burlywood","brown4","blue","bisque4","bisque",
"azure4","azure","aquamarine4","aquamarine","antiquewhite4","antiquewhite","aliceblue","dodgerblue4","dodgerblue","dimgrey",
"deepskyblue4", "deepskyblue", "deeppink4", "deeppink","darkviolet", "darkslategray4","darkslategray",
"darkseagreen4", "darkseagreen", "darksalmon", "darkred", "darkorchid4", "darkorchid", "darkorange4",
"darkorange","firebrick","darkgreen", "darkgoldenrod4","grey", "darkgoldenrod", "darkcyan")
V(g)$color <- colbar[fun.comps]
set.seed(123)
plot(g, edge.width=0.5,edge.color="grey", vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=3,margin=c(0, 0,0,0))
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
fung.module.net("SpMan",fq, abu,"Root","Control", 2, 9)
## [1] 0.346367
## Community sizes
## 1 2 3 4 5 6 7 8 9
## 22 28 24 7 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
## [1] 0.75
## Community sizes
## 1 2 3 4 5
## 4 3 2 2 2
fung.module.net("SpMan",fq, abu,"Root","Control", 8, 18)
## [1] 0.7318325
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12
## 8 7 5 16 12 3 3 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
## [1] 0.5361161
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14
## 9 6 12 11 3 9 4 3 2 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
## [1] 0.6985941
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
## 17 8 7 6 4 9 4 3 3 2 2 2 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
## [1] 0.4827387
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14
## 19 19 14 5 2 5 3 3 3 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
## [1] 0.3900327
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
## 67 28 11 26 4 2 4 3 2 2 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
## [1] 0.5292602
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14
## 39 27 4 3 3 2 2 2 2 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Soil","Control", 2, 9)
## [1] 0.6766205
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
## 15 7 5 4 9 6 3 3 2 2 2 2 2 2 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
## [1] 0.78738
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12
## 5 5 4 3 3 2 2 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Soil","Control", 8, 18)
## [1] 0.8655266
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 22 15 6 5 15 8 4 5 5 4 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2
## 27 28
## 2 2
fung.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
## [1] 0.8380582
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
## 8 6 10 6 5 4 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2
fung.module.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
## [1] 0.278699
## Community sizes
## 1 2 3 4 5
## 11 6 4 2 2
fung.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
## [1] 0.3234711
## Community sizes
## 1 2 3 4
## 9 5 3 7
fung.module.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
## [1] 0.6061801
## Community sizes
## 1 2 3 4
## 11 8 5 2
fung.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
## [1] 0.518338
## Community sizes
## 1 2 3 4 5 6 7 8
## 13 16 5 3 3 2 2 2
####################
# Module bac-bac###
####################
bac.module.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
da0<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
da <- da0[da0$Kingdom == "Prokaryote" & da0$Kingdom.1 == "Prokaryote",]
g <- graph.data.frame(da, directed=FALSE)
fun.fc<-cluster_fast_greedy(g)
print(modularity(fun.fc))
modularity(fun.fc,membership(fun.fc))
membership(fun.fc)
print(sizes(fun.fc))###
fun.comps <- membership(fun.fc)
colbar <-c("#0000FF","#FF3399","#FFCC33","#9999FF", "#FF99FF", "#FFFFCC",
"#33FFFF","#CCFF00","#CCFFCC","#FF3300","#CC99CC","#CC66CC","#FFFFCC","#CC0033","#666666","slateblue1","springgreen","steelblue1","tan1","thistle1","tomato","turquoise", "violet", "red", "yellowgreen", "peachpuff", "peru", "pink", "plum2", "purple","wheat", "cornsilk3","cornsilk","coral4","coral",
"chocolate4","chocolate","black","chartreuse4","chartreuse","burlywood4","burlywood","brown4","blue","bisque4","bisque",
"azure4","azure","aquamarine4","aquamarine","antiquewhite4","antiquewhite","aliceblue","dodgerblue4","dodgerblue","dimgrey",
"deepskyblue4", "deepskyblue", "deeppink4", "deeppink","darkviolet", "darkslategray4","darkslategray",
"darkseagreen4", "darkseagreen", "darksalmon", "darkred", "darkorchid4", "darkorchid", "darkorange4",
"darkorange","firebrick","darkgreen", "darkgoldenrod4","grey", "darkgoldenrod", "darkcyan")
V(g)$color <- colbar[fun.comps]
set.seed(123)
plot(g, edge.width=0.5,edge.color="grey", vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=3,margin=c(0, 0,0,0))
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
bac.module.net("SpMan",fq, abu,"Root","Control", 2, 9)
## [1] 0.4797443
## Community sizes
## 1 2 3 4 5 6 7 8 9 10
## 113 202 270 10 3 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
## [1] 0.7947377
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## 10 6 12 4 6 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Root","Control", 8, 18)
## [1] 0.4030565
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 97 176 8 7 9 6 3 3 4 3 3 2 3 2 2 2 2 2 2 2
## 21 22 23 24 25
## 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
## [1] 0.3857577
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12
## 247 159 69 2 2 3 3 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
## [1] 0.4598438
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 162 342 283 14 9 8 5 7 2 2 2 3 2 3 2 3 2 2 2 2
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
## [1] 0.7244696
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 24 47 51 18 17 11 5 5 7 3 4 3 4 3 3 3 3 3 2 2 2 2 2 2 2 2
## 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
## [1] 0.4066005
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 259 101 202 31 17 4 4 5 4 3 3 2 2 2 3 3 3 2 2 2
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
## [1] 0.3176892
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 309 157 196 55 5 4 6 3 2 2 2 2 2 2 2 2 2 2 2 2
## 21
## 2
bac.module.net("SpMan",fq, abu,"Soil","Control", 2, 9)
## [1] 0.6741034
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 101 85 157 24 16 13 12 9 6 6 5 5 5 4 4 4 3 4 3 3
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
## [1] 0.8345862
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 21 10 12 6 6 25 4 4 4 4 3 3 3 3 3 3 3 3 3 3 3 2 2 2 2 2
## 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Soil","Control", 8, 18)
## [1] 0.7438389
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 101 95 107 27 15 10 11 7 7 33 6 10 5 4 4 3 3 3 3 3
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 3 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 81 82 83
## 2 2 2
bac.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
## [1] 0.6792063
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 48 154 107 132 15 7 6 6 5 3 3 3 3 3 3 3 3 3 3 3
## 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40
## 3 3 3 3 3 2 3 3 2 2 2 2 2 2 2 2 2 2 2 2
## 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.module.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
## [1] 0.8347756
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12
## 8 9 6 3 4 3 3 3 2 2 2 2
bac.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
## [1] 0.600171
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13
## 15 12 16 16 11 4 4 3 3 3 2 2 2
bac.module.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
## [1] 0.2469185
## Community sizes
## 1 2 3 4 5 6 7 8 9 10
## 18 33 5 5 2 8 2 2 2 2
bac.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
## [1] 0.3142673
## Community sizes
## 1 2 3 4 5 6
## 34 53 45 2 2 2
####################
# Module bac-fung inter###
####################
bac.fung.inter.module.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
da0<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
da <- da0[da0$Kingdom != da0$Kingdom.1 ,]
g <- graph.data.frame(da, directed=FALSE)
fun.fc<-cluster_fast_greedy(g)
print(modularity(fun.fc))
modularity(fun.fc,membership(fun.fc))
membership(fun.fc)
print(sizes(fun.fc))###
fun.comps <- membership(fun.fc)
colbar <-c("#0000FF","#FF3399","#FFCC33","#9999FF", "#FF99FF", "#FFFFCC",
"#33FFFF","#CCFF00","#CCFFCC","#FF3300","#CC99CC","#CC66CC","#FFFFCC","#CC0033","#666666","slateblue1","springgreen","steelblue1","tan1","thistle1","tomato","turquoise", "violet", "red", "yellowgreen", "peachpuff", "peru", "pink", "plum2", "purple","wheat", "cornsilk3","cornsilk","coral4","coral",
"chocolate4","chocolate","black","chartreuse4","chartreuse","burlywood4","burlywood","brown4","blue","bisque4","bisque",
"azure4","azure","aquamarine4","aquamarine","antiquewhite4","antiquewhite","aliceblue","dodgerblue4","dodgerblue","dimgrey",
"deepskyblue4", "deepskyblue", "deeppink4", "deeppink","darkviolet", "darkslategray4","darkslategray",
"darkseagreen4", "darkseagreen", "darksalmon", "darkred", "darkorchid4", "darkorchid", "darkorange4",
"darkorange","firebrick","darkgreen", "darkgoldenrod4","grey", "darkgoldenrod", "darkcyan")
V(g)$color <- colbar[fun.comps]
set.seed(123)
plot(g, edge.width=0.5,edge.color="grey", vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=3,margin=c(0, 0,0,0))
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
bac.fung.inter.module.net("SpMan",fq, abu,"Root","Control", 2, 9)
## [1] 0.4599666
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
## 174 24 155 10 17 3 3 4 5 2 4 2 2 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
## [1] 0.78
## Community sizes
## 1 2 3 4 5 6 7
## 5 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Root","Control", 8, 18)
## [1] 0.5363242
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11
## 109 30 8 84 3 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
## [1] 0.3662968
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12
## 126 93 131 40 4 3 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
## [1] 0.4726193
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 81 60 21 28 66 25 8 5 5 4 3 4 3 3 3 3 3 3 3 3 3 2 2 2 2 2
## 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
## [1] 0.7581883
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 22 10 20 7 8 6 19 4 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 27 28 29 30 31
## 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
## [1] 0.5350336
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## 169 157 47 11 6 6 3 3 3 2 2 2 2 2 2 2 2 2 2 2
## 21 22 23 24 25
## 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
## [1] 0.2748164
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
## 169 46 75 141 5 9 4 3 2 2 2 2 2 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Soil","Control", 2, 9)
## [1] 0.7083955
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 41 9 13 4 31 24 6 5 4 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
## 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
## [1] 0.8596524
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## 10 9 6 4 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Soil","Control", 8, 18)
## [1] 0.8165966
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## 26 14 10 23 5 8 13 5 5 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
## [1] 0.7421026
## Community sizes
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
## 22 22 16 22 10 6 4 4 6 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2
## 27 28 29 30
## 2 2 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
## [1] 0.4444444
## Community sizes
## 1 2
## 3 2
bac.fung.inter.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
## [1] 0.5
## Community sizes
## 1 2
## 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
## [1] 0.5122991
## Community sizes
## 1 2 3 4
## 21 18 2 2
bac.fung.inter.module.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
## [1] 0.2612455
## Community sizes
## 1 2 3 4 5 6 7 8
## 18 34 28 10 4 2 2 2
##########
#Plotting##
###########
library(igraph)
bac.fung.cross.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
da<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
g <- graph.data.frame(da, directed=FALSE)
g.color = droplevels(ID.tmp[ID.tmp$OTU.ID %in% V(g)$name,])
g.color<-g.color[match(V(g)$name, g.color$OTU.ID),]
g.color$Kingdom1 <- factor(g.color$Kingdom, labels = c("blue", "black"))
levels(g.color$Kingdom1) = c("blue", "black")
V(g)$color = as.character(g.color$Kingdom1)
num.edges = length(E(g))
num.vertices = length(V(g))
connectance = edge_density(g,loops=FALSE)#
average.degree = mean(igraph::degree(g))#
average.path.length = average.path.length(g)
diameter = diameter(g, directed = FALSE, unconnected = TRUE, weights = NULL)
edge.connectivity = edge_connectivity(g)
clustering.coefficient = transitivity(g)
no.clusters = no.clusters(g)
centralization.betweenness = centralization.betweenness(g)$centralization
centralization.degree = centralization.degree(g)$centralization
fun.fc<-cluster_fast_greedy(g)
Modularity<-modularity(fun.fc,membership(fun.fc))
No.modules<-nrow(data.frame(sizes(fun.fc)))
df.tmp<-data.frame(network = "BF-FF-BB",type, habitat, treatment, tpA, tpB, num.edges, num.vertices, connectance, average.degree, average.path.length, diameter, edge.connectivity, clustering.coefficient,
no.clusters, centralization.betweenness,centralization.degree, Modularity, No.modules)
saveRDS(df.tmp, paste0("Fig.3/SpMan.network.property.2022.05.31/SpMan.network.property.BF.BB.FF.",type,".",habitat, ".", treatment,".",tpA,".",tpB,".RDS"))
g.E <-data.frame(get.edgelist(g))
names(g.E)<- c("V1", "V2")
V1<-data.frame("v1"=g.E$V1)
V2<-data.frame("v2"=g.E$V2)
ID.tmpx<-ID.tmp[,c("OTU.ID", "Kingdom")]
IDsub1<-ID.tmpx[ID.tmpx$OTU.ID %in% V1$v1, ]
IDsub2<-ID.tmpx[ID.tmpx$OTU.ID %in% V2$v2, ]
V1$id <- 1:nrow(V1); V2$id <- 1:nrow(V2)
M1<-merge(V1, IDsub1, by.x = "v1", by.y = "OTU.ID", all.x= T); M1<-M1[order(M1$id), ]
M2<-merge(V2, IDsub2, by.x = "v2", by.y = "OTU.ID", all.x = T); M2<-M2[order(M2$id), ]
M1$BF<-"red"
M1$BF[M1$Kingdom=="Prokaryote" & M2$Kingdom=="Prokaryote" ]<-"grey"
M1$BF[M1$Kingdom=="Eukaryote" & M2$Kingdom=="Eukaryote" ]<-"skyblue"
E(g)$color = as.character(M1$BF)
set.seed(123)
plot(g, edge.width=1, vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=3)
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
bac.fung.cross.net("SpMan",fq, abu,"Root","Control", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Root","Control", 8, 18)
bac.fung.cross.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
bac.fung.cross.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
bac.fung.cross.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
bac.fung.cross.net("SpMan",fq, abu,"Soil","Control", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Soil","Control", 8, 18)
bac.fung.cross.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
bac.fung.cross.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
bac.fung.cross.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
bac.fung.cross.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
################
##Inter-bac-Fung#
################
bac.fung.inter.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
ID.tmp$shape <- "circle"; ID.tmp$shape[ID.tmp$Kingdom=="Eukaryote"]<-"square"
ID.tmp$color <- "grey"
ID.tmp$color[ID.tmp$Funguild=="Plant pathogen"] <- "purple"
ID.tmp$color[ID.tmp$Funguild=="SaprotrophYeast"] <- "red"
ID.tmp$color[ID.tmp$Funguild=="Plant pathogenYeast"] <- "red"
ID.tmp$color[ID.tmp$Funguild=="Saprotroph"] <- "brown"
ID.tmp$color[ID.tmp$Funguild=="Arbuscular mycorrhizal"] <- "green"
ID.tmp$color[ID.tmp$Funguild=="Endophyte"] <- "blue"
ID.tmp$color[ID.tmp$Phylum=="Acidobacteria"] <- "blue"
ID.tmp$color[ID.tmp$Phylum=="Actinobacteria"] <- "red"
ID.tmp$color[ID.tmp$Phylum=="Bacteroidetes"] <- "black"
ID.tmp$color[ID.tmp$Phylum=="Proteobacteria"] <- "green"
ID.tmp$color[ID.tmp$Phylum=="Chloroflexi"] <- "brown"
ID.tmp$color[ID.tmp$Phylum=="Firmicutes"] <- "yellow"
ID.tmp$color[ID.tmp$Phylum=="Gemmatimonadetes"] <- "pink"
ID.tmp$color[ID.tmp$Phylum=="Verrucomicrobia"] <- "purple"
da0<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
da <- da0[da0$Kingdom != da0$Kingdom.1 ,]
g <- graph.data.frame(da, directed=FALSE)
g.color = droplevels(ID.tmp[ID.tmp$OTU.ID %in% V(g)$name,])
g.color<-g.color[match(V(g)$name, g.color$OTU.ID),]
V(g)$color = as.character(g.color$color)
V(g)$shape <-as.character(g.color$shape)
num.edges = length(E(g))
num.vertices = length(V(g))
connectance = edge_density(g,loops=FALSE)#
average.degree = mean(igraph::degree(g))#
average.path.length = average.path.length(g)
diameter = diameter(g, directed = FALSE, unconnected = TRUE, weights = NULL)
edge.connectivity = edge_connectivity(g)
clustering.coefficient = transitivity(g)
no.clusters = no.clusters(g)
centralization.betweenness = centralization.betweenness(g)$centralization
centralization.degree = centralization.degree(g)$centralization
fun.fc<-cluster_fast_greedy(g)
Modularity<-modularity(fun.fc,membership(fun.fc))
No.modules<-nrow(data.frame(sizes(fun.fc)))
df.tmp<-data.frame(network = "BF",type, habitat, treatment, tpA, tpB, num.edges, num.vertices, connectance, average.degree, average.path.length, diameter, edge.connectivity, clustering.coefficient,
no.clusters, centralization.betweenness,centralization.degree, Modularity, No.modules)
saveRDS(df.tmp, paste0("Fig.3/SpMan.network.property.2022.05.31/SpMan.network.property.BF.",type,".",habitat, ".", treatment,".",tpA,".",tpB,".RDS"))
g.E <-data.frame(get.edgelist(g))
names(g.E)<- c("V1", "V2")
V1<-data.frame("v1"=g.E$V1)
V2<-data.frame("v2"=g.E$V2)
ID.tmpx<-ID.tmp[,c("OTU.ID", "Kingdom")]
IDsub1<-ID.tmpx[ID.tmpx$OTU.ID %in% V1$v1, ]
IDsub2<-ID.tmpx[ID.tmpx$OTU.ID %in% V2$v2, ]
V1$id <- 1:nrow(V1); V2$id <- 1:nrow(V2)
M1<-merge(V1, IDsub1, by.x = "v1", by.y = "OTU.ID", all.x= T); M1<-M1[order(M1$id), ]
M2<-merge(V2, IDsub2, by.x = "v2", by.y = "OTU.ID", all.x = T); M2<-M2[order(M2$id), ]
M1$BF<-"red"
M1$BF[M1$Kingdom=="Prokaryote" & M2$Kingdom=="Prokaryote" ]<-"grey"
M1$BF[M1$Kingdom=="Eukaryote" & M2$Kingdom=="Eukaryote" ]<-"skyblue"
E(g)$color = as.character(M1$BF)
set.seed(123)
plot(g, edge.width=1, vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=5)
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
bac.fung.inter.net("SpMan",fq, abu,"Root","Control", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Root","Control", 8, 18)
bac.fung.inter.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
bac.fung.inter.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
bac.fung.inter.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
bac.fung.inter.net("SpMan",fq, abu,"Soil","Control", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Soil","Control", 8, 18)
bac.fung.inter.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
bac.fung.inter.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
bac.fung.inter.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
bac.fung.inter.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
##################
# Fungal network #
##################
fung.intra.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
ID.tmp$shape <- "circle"; ID.tmp$shape[ID.tmp$Kingdom=="Eukaryote"]<-"square"
ID.tmp$color <- "grey"
ID.tmp$color[ID.tmp$Funguild=="Plant pathogen"] <- "purple"
ID.tmp$color[ID.tmp$Funguild=="SaprotrophYeast"] <- "red"
ID.tmp$color[ID.tmp$Funguild=="Plant pathogenYeast"] <- "red"
ID.tmp$color[ID.tmp$Funguild=="Saprotroph"] <- "brown"
ID.tmp$color[ID.tmp$Funguild=="Arbuscular mycorrhizal"] <- "green"
ID.tmp$color[ID.tmp$Funguild=="Endophyte"] <- "blue"
da0<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
da <- da0[da0$Kingdom == "Eukaryote" & da0$Kingdom.1 == "Eukaryote",]
g <- graph.data.frame(da, directed=FALSE)
g.color = droplevels(ID.tmp[ID.tmp$OTU.ID %in% V(g)$name,])
g.color<-g.color[match(V(g)$name, g.color$OTU.ID),]
V(g)$color = as.character(g.color$color)
V(g)$shape <-as.character(g.color$shape)
num.edges = length(E(g))
num.vertices = length(V(g))
connectance = edge_density(g,loops=FALSE)#
average.degree = mean(igraph::degree(g))#
average.path.length = average.path.length(g)
diameter = diameter(g, directed = FALSE, unconnected = TRUE, weights = NULL)
edge.connectivity = edge_connectivity(g)
clustering.coefficient = transitivity(g)
no.clusters = no.clusters(g)
centralization.betweenness = centralization.betweenness(g)$centralization
centralization.degree = centralization.degree(g)$centralization
fun.fc<-cluster_fast_greedy(g)
Modularity<-modularity(fun.fc,membership(fun.fc))
No.modules<-nrow(data.frame(sizes(fun.fc)))
df.tmp<-data.frame(network = "FF",type, habitat, treatment, tpA, tpB, num.edges, num.vertices, connectance, average.degree, average.path.length, diameter, edge.connectivity, clustering.coefficient,
no.clusters, centralization.betweenness,centralization.degree, Modularity, No.modules)
saveRDS(df.tmp, paste0("Fig.3/SpMan.network.property.2022.05.31/SpMan.network.property.FF.",type,".",habitat, ".", treatment,".",tpA,".",tpB,".RDS"))
g.E <-data.frame(get.edgelist(g))
names(g.E)<- c("V1", "V2")
V1<-data.frame("v1"=g.E$V1)
V2<-data.frame("v2"=g.E$V2)
ID.tmpx<-ID.tmp[,c("OTU.ID", "Kingdom")]
IDsub1<-ID.tmpx[ID.tmpx$OTU.ID %in% V1$v1, ]
IDsub2<-ID.tmpx[ID.tmpx$OTU.ID %in% V2$v2, ]
V1$id <- 1:nrow(V1); V2$id <- 1:nrow(V2)
M1<-merge(V1, IDsub1, by.x = "v1", by.y = "OTU.ID", all.x= T); M1<-M1[order(M1$id), ]
M2<-merge(V2, IDsub2, by.x = "v2", by.y = "OTU.ID", all.x = T); M2<-M2[order(M2$id), ]
M1$BF<-"red"
M1$BF[M1$Kingdom=="Prokaryote" & M2$Kingdom=="Prokaryote" ]<-"grey"
M1$BF[M1$Kingdom=="Eukaryote" & M2$Kingdom=="Eukaryote" ]<-"skyblue"
E(g)$color = as.character(M1$BF)
set.seed(123)
plot(g, edge.width=1, vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=5)
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
fung.intra.net("SpMan",fq, abu,"Root","Control", 2, 9)
fung.intra.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
fung.intra.net("SpMan",fq, abu,"Root","Control", 8, 18)
fung.intra.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
fung.intra.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
fung.intra.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
fung.intra.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
fung.intra.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
fung.intra.net("SpMan",fq, abu,"Soil","Control", 2, 9)
fung.intra.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
fung.intra.net("SpMan",fq, abu,"Soil","Control", 8, 18)
fung.intra.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
fung.intra.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
fung.intra.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
fung.intra.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
fung.intra.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
####################
#Bacterial network##
####################
bac.intra.net<-function(type,fq, abu, habitat, treatment, tpA, tpB){
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
ID.tmp$shape <- "circle"; ID.tmp$shape[ID.tmp$Kingdom=="Eukaryote"]<-"square"
ID.tmp$color <- "grey"
ID.tmp$color[ID.tmp$Phylum=="Acidobacteria"] <- "blue"
ID.tmp$color[ID.tmp$Phylum=="Actinobacteria"] <- "red"
ID.tmp$color[ID.tmp$Phylum=="Bacteroidetes"] <- "black"
ID.tmp$color[ID.tmp$Phylum=="Proteobacteria"] <- "green"
ID.tmp$color[ID.tmp$Phylum=="Chloroflexi"] <- "brown"
ID.tmp$color[ID.tmp$Phylum=="Firmicutes"] <- "yellow"
ID.tmp$color[ID.tmp$Phylum=="Gemmatimonadetes"] <- "pink"
ID.tmp$color[ID.tmp$Phylum=="Verrucomicrobia"] <- "purple"
da0<-readRDS(paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/",type,".Rsig.Bac-Fung.",habitat,".", treatment,".",tpA,".",tpB,".",fq,".",abu,".RDS"))
da <- da0[da0$Kingdom == "Prokaryote" & da0$Kingdom.1 == "Prokaryote",]
g <- graph.data.frame(da, directed=FALSE)
g.color = droplevels(ID.tmp[ID.tmp$OTU.ID %in% V(g)$name,])
g.color<-g.color[match(V(g)$name, g.color$OTU.ID),]
V(g)$color = as.character(g.color$color)
V(g)$shape <-as.character(g.color$shape)
num.edges = length(E(g))
num.vertices = length(V(g))
connectance = edge_density(g,loops=FALSE)#
average.degree = mean(igraph::degree(g))#
average.path.length = average.path.length(g)
diameter = diameter(g, directed = FALSE, unconnected = TRUE, weights = NULL)
edge.connectivity = edge_connectivity(g)
clustering.coefficient = transitivity(g)
no.clusters = no.clusters(g)
centralization.betweenness = centralization.betweenness(g)$centralization
centralization.degree = centralization.degree(g)$centralization
fun.fc<-cluster_fast_greedy(g)
Modularity<-modularity(fun.fc,membership(fun.fc))
No.modules<-nrow(data.frame(sizes(fun.fc)))
df.tmp<-data.frame(network = "BB",type, habitat, treatment, tpA, tpB, num.edges, num.vertices, connectance, average.degree, average.path.length, diameter, edge.connectivity, clustering.coefficient,
no.clusters, centralization.betweenness,centralization.degree, Modularity, No.modules)
saveRDS(df.tmp, paste0("Fig.3/SpMan.network.property.2022.05.31/SpMan.network.property.BB.",type,".",habitat, ".", treatment,".",tpA,".",tpB,".RDS"))
g.E <-data.frame(get.edgelist(g))
names(g.E)<- c("V1", "V2")
V1<-data.frame("v1"=g.E$V1)
V2<-data.frame("v2"=g.E$V2)
ID.tmpx<-ID.tmp[,c("OTU.ID", "Kingdom")]
IDsub1<-ID.tmpx[ID.tmpx$OTU.ID %in% V1$v1, ]
IDsub2<-ID.tmpx[ID.tmpx$OTU.ID %in% V2$v2, ]
V1$id <- 1:nrow(V1); V2$id <- 1:nrow(V2)
M1<-merge(V1, IDsub1, by.x = "v1", by.y = "OTU.ID", all.x= T); M1<-M1[order(M1$id), ]
M2<-merge(V2, IDsub2, by.x = "v2", by.y = "OTU.ID", all.x = T); M2<-M2[order(M2$id), ]
M1$BF<-"red"
M1$BF[M1$Kingdom=="Prokaryote" & M2$Kingdom=="Prokaryote" ]<-"grey"
M1$BF[M1$Kingdom=="Eukaryote" & M2$Kingdom=="Eukaryote" ]<-"skyblue"
E(g)$color = as.character(M1$BF)
set.seed(123)
plot(g, edge.width=1, vertex.frame.color=NA,vertex.label=NA,edge.lty=1, edge.curved=T,vertex.size=5)
}
par(mfrow=c(4,4),mar=c(0, 0, 0, 0))
bac.intra.net("SpMan",fq, abu,"Root","Control", 2, 9)
bac.intra.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 2, 9)
bac.intra.net("SpMan",fq, abu,"Root","Control", 8, 18)
bac.intra.net("SpMan",fq, abu,"Root","Pre_flowering_drought", 8, 18)
bac.intra.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
bac.intra.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
bac.intra.net("SpMan",fq, abu,"Rhizosphere","Control", 8, 18)
bac.intra.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 8, 18)
bac.intra.net("SpMan",fq, abu,"Soil","Control", 2, 9)
bac.intra.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 2, 9)
bac.intra.net("SpMan",fq, abu,"Soil","Control", 8, 18)
bac.intra.net("SpMan",fq, abu,"Soil","Pre_flowering_drought", 8, 18)
bac.intra.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
bac.intra.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
bac.intra.net("SpMan",fq, abu,"Leaf","Control", 8, 18)
bac.intra.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 8, 18)
par(mfrow=c(2,2),mar=c(0, 0, 0, 0))
fung.intra.net("SpMan",fq, abu,"Rhizosphere","Control", 2, 9)
fung.intra.net("SpMan",fq, abu,"Rhizosphere","Pre_flowering_drought", 2, 9)
bac.intra.net("SpMan",fq, abu,"Leaf","Control", 2, 9)
bac.intra.net("SpMan",fq, abu,"Leaf","Pre_flowering_drought", 2, 9)
library(tidyverse)
type = "SpMan"
mydir = paste0("Fig.3/BFT.",type,".sig.df.2022.05.31/")
da <- list.files(path=mydir, full.names=TRUE) %>% map_dfr(readRDS)
BF0<-read.csv("Microbiome/0000BacteriaFungi.1029x1293.13165.2019.07.10.csv", head = T, row.names = 1)
ID.tmp<-BF0[,c("Kingdom", "Kingdom1", "Phylum", "Class", "Order", "Family", "Genus", "Funguild", "OTU.ID", "Morph", "Morph1")]
da.fung <- droplevels(da[da$Kingdom == "Eukaryote" & da$Kingdom.1 == "Eukaryote" & da$Habitat == "Rhizosphere" & da$TPA ==2,])
da.fung$interaction<-"Inter-Guilds"
da.fung$interaction[da.fung$Funguild==da.fung$Funguild.1]<-"Intra-Guild"
da.fung$ab<-1
lev<-interaction(da.fung$interaction, da.fung$Treatment, da.fung$TPA, da.fung$Habitat,sep = ":") ## ccombining factors for Barplot profiling
da1<-aggregate(da.fung$ab,by=list(lev) , sum) # generate the mean for each factor level
library(splitstackshape)
dax.fung<-cSplit(da1, "Group.1", ":")
names(dax.fung)<-c("abu", "interaction","Treatment", "tpA", "Habitat")
dax.fung$Treatment<- factor(dax.fung$Treatment, labels=c("Control", "Drought"))
g1 <- ggplot(dax.fung, aes(x = Treatment, y = abu, fill= interaction)) +
geom_bar(stat='identity', position = "fill")+
theme_bw()+xlab("")+ylab("Proportion")+
scale_fill_manual(values = c("purple", "pink"))+
ggtitle("Rhizosphere: FF")+
theme(plot.title = element_text(size = 12,face="bold",hjust=0.5),
strip.text = element_text(size = 10,face="bold"),
legend.title = element_blank(),
legend.text = element_text(colour="black", size=10, face="bold"),
axis.text.y=element_text(size=10,colour="black",face="bold"),
axis.text.x=element_text(size=10,colour="black",face="bold",angle = 45),
axis.title=element_text(size=10,colour="black",face="bold"))+
scale_y_continuous(labels = scales::percent)
da.bac <- da[da$Kingdom == "Prokaryote" & da$Kingdom.1 == "Prokaryote" & da$Habitat == "Leaf" & da$TPA ==2,]
da.bac$interaction<-"Inter-Phyla"
da.bac$interaction[da.bac$Phylum==da.bac$Phylum.1]<-"Intra-Phylum"
da.bac$ab<-1
lev<-interaction(da.bac$interaction, da.bac$Treatment, da.bac$TPA, da.bac$Habitat,sep = ":") ## ccombining factors for Barplot profiling
da1<-aggregate(da.bac$ab,by=list(lev) , sum) # generate the mean for each factor level
library(splitstackshape)
dax.bac<-cSplit(da1, "Group.1", ":")
names(dax.bac)<-c("abu", "interaction","Treatment", "tpA", "Habitat")
dax.bac$Treatment<- factor(dax.bac$Treatment, labels=c("Control", "Drought"))
g2 <- ggplot(dax.bac, aes(x = Treatment, y = abu, fill= interaction)) +
geom_bar(stat='identity', position = "fill")+
theme_bw()+xlab("")+ylab("Proportion")+
scale_fill_manual(values = c("purple", "pink"))+
ggtitle("Leaf: BB")+
theme(plot.title = element_text(size = 12,face="bold",hjust=0.5),
strip.text = element_text(size = 10,face="bold"),
legend.title = element_blank(),
legend.text = element_text(colour="black", size=10, face="bold"),
axis.text.y=element_text(size=10,colour="black",face="bold"),
axis.text.x=element_text(size=10,colour="black",face="bold",angle = 45),
axis.title=element_text(size=10,colour="black",face="bold"))+
scale_y_continuous(labels = scales::percent)
library(gridExtra)
grid.arrange(g1,g2)
